30 Most Useful Python Libraries for Web Development in 2024

Discover the top Python libraries that will aid you in 2024. From data analysis to web development, find everything you need for efficient programming in Python.

30 Most Useful Python Libraries for Web Development in 2024

If you're just starting to develop your first website using Python, this article will help you understand which Python libraries and tools are essential, and what criteria to consider when choosing tools.

Universally Useful for All Frameworks

Even if not all tools are immediately clear or necessary, save this listing for future reference: tools like gunicorn may become essential as you progress.

• Pillow: A library for working with images. The built-in Python module isn't sufficient, so "Pillow" becomes a necessity.
• psycopg: One of the best PostgreSQL adapters for Python. As soon as a developer delves into databases in production, they quickly realize that PostgreSQL is the go-to. Tools trying to outdo it create killer features, but its established reputation is hard to ignore. psycopg allows me to access my article database on PostgreSQL from the command line on the deployment service Railway and quickly update content.
• python-dateutil: An extension for the standard datetime module, providing convenient date and time manipulations. Temporal formats are a pain for developers, not just Pythonistas. Therefore, pay attention to these "workhorses". Adequate and painless handling of dates and times is essential for any site.
• bootstrap-icons: An npm package attachable to an HTML template via CDN link, providing a collection of 2000+ icons in Material Design style.
• tzdata: A utility with time zone information used with datetime and others.
• urllib3: For making requests to web servers, such as downloading from a server or reading data from an API.
• requests: One of the most popular libraries for making HTTP requests in Python. If you need to make API requests, start here. It's well-covered on Stack Overflow, increasing the chances of troubleshooting. If you're familiar with async programming, httpx/asyncio are also great choices.
• sqlparse: Suitable for formatting and parsing SQL queries. When publishing an article via the Django admin panel, this library "tidies up" GET/POST/DELETE requests.
• pandas: Likely you'll add this tool yourself. This library "rotates" your tabular data in any direction. In 2024, experienced Python developers are also exploring polars.
• certbot: Free SSL certificates. Without it, your site's traffic will plummet as browsers display a warning about an unsafe site.
• plotly: Designer graphics with fine-tuning of almost any aspect. If a function lacks a parameter to gradient the Y-axis color, you can add it! Open Source allows you to tailor it exactly to your needs. Hardcore designers might prefer matplotlib.
• FastAPI: A modern, fast (based on ASGI) web framework for creating APIs with automatic OpenAPI documentation generation and parallelism support. FastAPI is well-covered on Stack Overflow, making it a good starting point. Experimenters may try LiteStar, which integrates well with LLM.
• pytest: The fastest way to write tests for your functions. Though often neglected in early projects, testing becomes crucial in a professional IT environment.
• gunicorn: A server for running Python web applications. An unassuming but vital participant in the listing.
• six: A library for ensuring compatibility between Python 2 and 3. When borrowing ready-made templates, ensure Python is version 3.x.x.
• PyYAML: A human-readable configuration format. Often enters your life subtly through tools like Docker.

  # config.yaml
  server:
    host: "0.0.0.0"
    port: 8080
  database:
    type: "postgresql"
    host: "localhost"
    port: 5432
    username: "db_user"
    password: "db_password"
    database_name: "mydatabase"
  logging:
    level: "DEBUG"
    file: "app.log"
  api_keys:
    google_maps: "YOUR_GOOGLE_MAPS_API_KEY"
    stripe: "YOUR_STRIPE_API_KEY"
  

• wheel: Speeds up the installation of libraries and modules. If you're developing on Windows and hosting on Linux, wheel accelerates deployment.
• charset-normalizer: Manages text encoding to save you from encoding nightmares.
• typing-extensions: Enables type annotations, crucial for specifying data types in your code.

  from typing_extensions import Annotated
  
  def greet(name: Annotated[str, "Name"]) -> None:
      print(f"Hello, {name}")
  

• cryptography: Encryption and hashing—protects your data from unauthorized access.

  >>> from cryptography.hazmat.primitives import hashes
  >>> digest = hashes.Hash(hashes.SHA256())
  >>> digest.update(b'Message to hash')
  >>> hash_value = digest.finalize()
  >>> print(f'SHA-256 Hash: {hash_value.hex()}')
  

• fsspec: Unifies file access across operating systems. Consistently handles file paths regardless of OS.
• MarkupSafe: Safely renders HTML/XML text.
• python-slugify: Creates friendly URLs for uniform pages, like encyclopedia articles.

  >>> from slugify import slugify
  >>> slugify("Some Article Title")
  'some-article-title'
  

Django Essentials

• django-tailwind: Integrates the Tailwind CSS framework with Django. Useful for quick, stylish design without extensive effort.
• django-tinymce: Integrates the TinyMCE WYSIWYG editor with Django, providing minimalistic but effective text formatting tools.
• django_mathjax: Integrates MathJax for rendering mathematical formulas.
• django-orm: Allows your project to switch from SQLite to PostgreSQL (or other SQL databases), useful for developing on a small PC while deploying a large database in production.
• django-js-asset: Manages JavaScript file dependencies.

Conclusion

Choosing the right tech stack is a challenge for beginners. While standard site features like feedback forms and CDN images might occupy your initial focus, selecting libraries can be daunting. Use the common solutions recommended here, but tailor them to your project's needs. Large Language Models (LLMs) like ChatGPT can help suggest well-established solutions, making the process smoother.